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Solving Unit Commitment Problem Using Modified Subgradient Method Combined with Simulated Annealing Algorithm

机译:改进次梯度法结合模拟退火算法求解机组组合问题

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This paper presents the solving unit commitment (UC) problem using Modified Subgradient Method (MSG) method combined with Simulated Annealing (SA) algorithm. UC problem is one of the important power system engineering hard-solving problems. The Lagrangian relaxation (LR) based methods are commonly used to solve the UC problem. The main disadvantage of this group of methods is the difference between the dual and the primal solution which gives some significant problems on the quality of the feasible solution. In this paper, MSG method which does not require any convexity and differentiability assumptions is used for solving the UC problem. MSG method depending on the initial value reaches zero duality gap. SA algorithm is used in order to assign the appropriate initial value for MSG method. The major advantage of the proposed approach is that it guarantees the zero duality gap independently from the size of the problem. In order to show the advantages of this proposed approach, the four-unit Tuncbilek thermal plant and ten-unit thermal plant which is usually used in literature are chosen as test systems. Penalty function (PF) method is also used to compare with our proposed method in terms of total cost and UC schedule.
机译:本文提出了采用改进次梯度法(MSG)和模拟退火(SA)算法相结合的求解单元承诺(UC)问题。 UC问题是电力系统工程解决的重要问题之一。基于拉格朗日松弛(LR)的方法通常用于解决UC问题。这组方法的主要缺点是对偶解和原始解之间的差异,这给可行解的质量带来了一些重大问题。本文采用不需要凸和微分假设的MSG方法来解决UC问题。 MSG方法根据初始值达到零对偶间隙。 SA算法用于为MSG方法分配适当的初始值。所提出的方法的主要优点是,它保证了零对偶间隙与问题的大小无关。为了显示该方法的优点,选择文献中通常使用的四单元Tuncbilek热电厂和十单元热电厂作为测试系统。在总成本和UC进度方面,还使用了惩罚函数(PF)方法与我们提出的方法进行比较。

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